[petsc-users] Parallel processes run significantly slower

[Steffen Wilksen | Universitaet Bremen]

Hi all,

I'm trying to do repeated matrix-vector-multiplication of large sparse  
matrices in python using petsc4py. Even the most simple method of  
parallelization, dividing up the calculation to run on multiple  
processes indenpendtly, does not seem to give a singnificant speed up  
for large matrices. I constructed a minimal working example, which I  
run using

mpiexec -n N python parallel_example.py,

where N is the number of processes. Instead of taking approximately  
the same time irrespective of the number of processes used, the  
calculation is much slower when starting more MPI processes. This  
translates to little to no speed up when splitting up a fixed number  
of calculations over N processes. As an example, running with N=1  
takes 9s, while running with N=4 takes 34s. When running with smaller  
matrices, the problem is not as severe (only slower by a factor of 1.5  
when setting MATSIZE=1e+5 instead of MATSIZE=1e+6). I get the same  
problems when just starting the script four times manually without  
using MPI.
I attached both the script and the log file for running the script  
with N=4. Any help would be greatly appreciated. Calculations are done  
on my laptop, arch linux version 6.6.8 and PETSc version 3.20.2.

Kind Regards
Steffen
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